Computations of quantum eigenstates via deep neural networks (Spring 2024)
Computations of quantum eigenstates via deep neural networks (Spring 2024)
The eigenstates for a quantum structure provide valuable information for the properties for a material. Traditionally, the eigenstates are computed by solving the Schrödinger equation. However, the computational cost becomes exhibitive in high dimensions. This project aims to develop a new algorithm using deep neural networks to solve this eigenvalue problem directly via optimization. We will first apply the new algorithm on hydrogen atom and then on more complicated structures.
For more information contact Xiaokai Huo (xhuo@iastate.edu)
People:
People:
Xiaokai Huo (Postdoc)
Pre-requisites:
Pre-requisites:
Knowlege of calculus and linear algebra.
Programming skills (Python) are desired but not required